4.
The Effects of the Lack of Sanitation in the Lives of Women

 
 
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As seen in the previous chapter, the occurrence of gastrointestinal infections led to the absence of Brazilian women from their routine activities. Depending on the severity, the infections led to bed rest or hospitalization. In more acute cases, it was the cause of death. But in all cases, infections have alienated women from their study and from their economic or domestic activities, and have increased their hours dedicated to the health care of relatives (children, spouses, parents, etc.). In this sense, infections associated with lack of basic sanitation have affected the lives of women of all ages, races and social classes, with effects on their present and future income and on the hours available for rest or leisure. In other words, the lack of sanitation brought losses of well-being to Brazilian women.

This chapter of the study examines the impacts of poor sanitation on the lives of women students and those engaged in paid economic activities. The analysis is developed based on data from the National Continuous Household Sample Survey (PNADC) of 2016 and the National High School Examination (ENEM) of 2016. In order to facilitate the exposition and understanding, the chapter is organized according to the participation of women as students or as persons engaged in economic activity. However, it should not be forgotten that there are women who, in their daily lives, regularly carry out these activities together.

 
 
 

Dedication to Studies

 
 
 

In 2016, according to PNADC data, there were 25.373 million women attending regular courses. That means that one in four women was studying in that year. In the North, Northeast and Midwest regions, where the female population was relatively younger, the percentages of total females that were studying were higher. The frequency statistics for courses are shown in Table A.11 of the Statistical Annex, by unit of the Federation, region and household region.

Just over half (54.2%) of the female population that was studying in 2016 attended elementary school and another 6.0% were in pre-school or literacy courses. This indicates that 6 out of 10 students attended basic curriculum courses. In addition to this group, about 20% of students were enrolled in high school. The other fifth part of the Brazilian students was attending higher education, including undergraduate and postgraduate courses (specialization, master and doctorate).

Graph 4.1
Distribution of Brazilian students by course, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

It is important to note that, even considering the current structures to encourage the inclusion of vulnerable social groups in higher education, the participation of black or indigenous women was still very small. Only 15.0% of multiracial self-reported students were attending college. The majority (64.4%) attended basic education (elementary, pre-school and literacy). Among the self-taught black and indigenous students the situation was similar. Among the self-declared of Asian descent students, the situation was different: 38.6% were attending higher education courses and only 38.1% were in elementary education. These data show that the progression in the teaching of black and indigenous Brazilian self-declared women was much smaller than the progression of those who declared themselves white and of Asian-descent.

Graph 4.2
Distribution of Brazilian students by course level and self-declared race, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

The progression in education was also significantly lower among students who belonged to the poorest 20% of the country. In this per capita household income class, 3 out of 4 students were enrolled in basic education, and only 4.4% of students attended higher education. Among the students who belonged to the richest 20% of the Brazilian population, the situation was totally different: almost half of the students were in higher education courses and only 37.8% of the women were enrolled in elementary education.

Graph 4.3
Distribution of Brazilian students by course level and income distribution quintile, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Another striking difference between classes is participation in public and private schools. Among students who were among the richest 20% of the Brazilian population, attendance in private schools reached almost 70%. Among students who were in the poorest 20% of the Brazilian population, 93.0% attended public schools.

Graph 4.4
Distribution of Brazilian students by educational network and quintile of income distribution, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

The conditions of these students' homes, in particular the conditions of access to basic sanitation, had an effect on their school performance and progression in the study. Several Brazilian studies have sought to establish and evidence these relationships. The study of the Center for Social Policies (CPS-FGV, 2008), on one hand, evaluated the effect of basic sanitation on school achievement, understood as the rate of progression in education. The Instituto Trata Brasil study (2017), on the other hand, evaluated the effect of access to sanitation on school delay based on information from the 2015 PNAD (IBGE, 2016). School delay was defined as the difference between schooling reached by school-age people and the number of years of study they could have considered their respective ages.

The statistical analysis developed in this study on sanitation and Brazilian women complements and deepens these assessments by identifying the effect of access to sanitation on school delay and school performance of the female population in Brazil. Students being behind in school years is considered a problem because it conditions the performance of younger people in their economic activities, signaling a lower potential for increased productivity and pay for future generations. But there is another more immediate effect of the lack of sanitation on Brazilian women who are students: sanitation interferes with the chances of progression to higher education and the qualification of young women who have recently entered the labor market. This is because sanitation affects school performance in terms of grades.

The analysis of the effect of sanitation on the delay was developed based on information from the PNADC of 2016 (IBGE, 2017). In the present study, the population aged between 5 and 19 years old was considered to be of school age. For this age group, the school delay was calculated, with its determinants investigated through statistical models. The statistics on the school lag of the female population are presented in regional detail in Table A.12 of the Statistical Annex.

Indicators of school lag in Brazil show strong gender and racial inequality among Brazilian youths by 2016. In general, women had a lower school delay than men (3.8 years versus 4.1 years), indicating that women , on average, were less behind in the studies than men. On the other hand, it is seen that self-reported indigenous, black or brown women had much higher levels of school delay than white or yellow self-declared women. This fact reflects, at least in part, the differences that were identified in the progression in teaching among Brazilian students.

Graph 4.5
School delay by gender and self-declared race, in years, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

But there are other factors that interfere in the determination of school lag. When comparing the averages of school delay of people living in households with access to sanitation, whether they are girls or boys, with the average of people living in homes without access to sanitation, it's possible to note the importance of this basic infrastructure in the life of young Brazilians. Young people receiving in their homes water distributed through the general network had lower averages of school delay. Those who lived in residences with sewage collection also had lower averages of school delay. The biggest difference was seen in the case of the existence of bathroom for exclusive use in the household. On average, young women living in houses with exclusive-use bathrooms had 1.2 years of school delay less than those living in homes without a bathroom. In percentage terms, the difference in this case reached 17.6%.

Graph 4.6
School Delay by Gender and Availability of Infrastructure Services, in Years, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

The statistical model developed in this study, which is presented in detail in the Methodological Annex, isolated the effect of sanitation on school delay in the young population of the country. It was found that the children and young people who lived in areas without access to sewage collection services had, on average, a school delay 1.5% higher than those who lived in places with sewage collection. Those who lived in areas without access to the water distribution network had, on average, a school delay 1.1% higher than that of children and young people living in areas with access to the general water supply network. Among young people living in homes without a bathroom, the expected school delay was 7.3% higher than the average for young people living in bathrooms.

One consequence of this finding is the fact that women, children or youth, without access to basic sanitation will be less educated than others when entering the labor market. Since schooling positively affects the productivity and income of female workers (1 For each additional year of study, Brazilian female workers have, on average, a 4.8% increase in their remuneration. This aspect will be discussed in more detail in the next section), a lower level of schooling will mean a loss of productivity and job remuneration. On the other hand, if a student who does not have access to sanitation services is given access to sanitation services, a reduction of up to 10% in school delay is expected, allowing an increase in schooling. Thus, access to sanitation has the potential to raise the productivity of future generations of workers, with a positive effect on their pay.

In order to analyze the issue of school performance, the present study on the Brazilian women analyzed the results of the National High School Examination (ENEM) of 2016. In this analysis, the results of the ENEM tests were used in a database containing information on almost 8.4 million students enrolled in that year's exam. Of this total, 4.263 million young people were set aside followed the criteria: (i) they completed the exam and scored in all tests, (ii) were not enrolled as 'trainees' and (iii) were between 15 and 29 years old, that is, that they would possibly seek vacancies in higher education or would seek a placement in the labor market in 2017.

Of the total number of young people analyzed, 2.423 million were women (56.8% of the total) and 1.840 million were men (43.2%). What stands out first is the fact that women had lower scores on average than the young men in the four objective tests of ENEM - Natural Sciences, Humanities, Languages and Codes and Mathematics. In the math test, the difference between genders reached almost 40 points. However in the essay writing, women had superior performance: on average, their grades were 28.6 points above that achieved by men. Nevertheless, considering the simple average of the five grades, the women registered an average score 8.9 points lower than the average of the men. Map 4.1 shows the average scores of women by region of the country in the ENEM of 2016. Another fact that draws attention is the difference of performance between the students of the public network and the private network of schools. Those enrolled from the public school system had an average grade of 493.2 points while those from the private school network averaged 583.9 points. There was, therefore, a difference of 90.7 points between the two groups. The largest differences were recorded in the essay writing, a test in which the enrollees coming from the public network had an average that was 144.2 points below the average of those coming from the private network, and in the math test, in which the difference reached 97.4 points.

Graph 4.7
Grades in the ENEM, by race and gender, 2016

Source: INEP, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: INEP, 2017. Elaboration: Ex Ante Consultoria Econômica.

Graph 4.8
Grades in the ENEM tests, by test and school network, female population, 2016

Source: INEP, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: INEP, 2017. Elaboration: Ex Ante Consultoria Econômica.

Graph 4.9
Grades in the ENEM tests, by test and availability of bathroom, female population, 2016

Source: INEP, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: INEP, 2017. Elaboration: Ex Ante Consultoria Econômica.

Map 4.1
Average grade * obtained in the National High School Examination, female population, 2016

Source: INEP, 2017 (*) Simple average of the four objective tests and the essay. Elaboration: Ex Ante Consultoria Econômica.

Source: INEP, 2017 (*) Simple average of the four objective tests and the essay. Elaboration: Ex Ante Consultoria Econômica.

Observing the data, access to sanitation again is a determining variable. Considering only the female population, all the averages of women living in houses without a private bathroom were below the averages of women living in bathrooms. Again, the biggest differences occurred in the essays (-65.6 points) and math test (-36.5 points).

In order to confirm this relationship, and to calculate the partial effect of basic sanitation on the average performance of those enrolled in the exam, statistical models were developed for the determinants of ENEM scores, by test and for the mean of the tests. The models, which are presented in detail in the Methodological Annex, in addition to the existence of a bathroom at home, take into account various information about the students: gender, place of residence, type of school that they attended, high school they attended, age, declared race, education levels of their parents, family income range and the existence of a washing machine in the house. The existence of a washing machine, in the present context, functions as a proxy to identify homes that have a piped water network and which have electricity (two pre-conditions for the appliance to function).

The estimated partial effects prove some of the ideas developed earlier. The female population analyzed performed slightly lower than the male population. Those enrolled at public schools also presented inferior performance and the highest grades were obtained by young people aged 16 or 17 years old. Among women, self-reported black and multiracial had lower scores than self-reported white and of Asian descent; the indigenous had even lower grades. As expected, grades increased according to per capita household income class and parental schooling levels. People who lived in houses without a bathroom or without a washing machine had much lower scores than those who lived in houses with a bathroom or a washing machine. These effects were even more intense in the case of women.

Table 4.1 shows the expected differences in grades relative to the ENEM average considering the female gender, the self-declared race, and the availability of bathroom and washing machine in the household. Estimates show that, considering the other factors as constant, a woman is expected to have a score of 9 points lower than the average of the exam. If this woman resides in a house without a bathroom, she is expected to have a score of 45.7 points lower than the average of the examination. If this woman resides in a house without a washing machine, the mark should be 31.0 points lower than the average. In case the woman does not have a bathroom or washing machine in her house, she is expected a 67.7 point lower than average score. In the case of self-reported black, multiracial or indigenous women these differences are extremely high.

Table 4.1
Differential scores obtained by women* on the ENEM 2016 in relation to the average, by test and self-declared race

Natural SciencesHumanitiesLanguages and CodesMathEssaySum
Women*-13.2-6.94.633.940.39.0
Women who live at a home without a bathroom-15.7-13.9-3.3-35.322.5-45.7
Womem who live in households without a washing machine-16.8-11.31.1-35.431.5-31.0
Black self-declared women-22.7-11.5-1.2-51.431.455.4
Black self-declared women who live at a home without a bathroom-25.2-18.5-9.1-52.813.5-92.1
Black self-declared women who live in households without a washing machine-26.4-15.9-4.7-53.022.5-77.4
Multiracial self-declared women-20.4-13.2-1.9-44.331.0-48.8
Multiracial self-declared women who live at a home without a bathroom-22.9-20.2-9.7-45.813.2-85.4
Multiracial self-declared women who live in households without a washing machine-24.1-17.6-5.3-45.922.1-70.8
Indigenous self-declared women -29.9-26.2-14.7-58.92.1-127.6
Indigenous self-declared women who live at a home without a bathroom-32.4-33.2-22.5-60.4-15.7-164.2
Indigenous self-declared women who live in households without a washing machine-33.6-30.6-18.2-60.5-6.8-149.6

Source: INEP, 2017 (*) Women aged between 14 and 29 years old. Elaboration: Ex Ante Consultoria Econômica.


This analysis reveals that school performance is affected by sanitation conditions, which interfere even more intensely with Brazilian girls and young women. As the national examination grades are used both for the selection of students in public higher education (SISU) and for the granting of scholarships in the federal programs of development programs - University for All Program (Prouni) and Student Funding Program (FIES), it can be concluded that lack of sanitation has a negative effect on women's chances of progressing to free public higher education.

Graph 4.10
Grades in the tests of the National Examination of High School and access to sanitation, units of the Federation, female population, 2016

BRK_MeS_Graph_4_10A_af.png
Source: INEP, 2017 and IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: INEP, 2017 and IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

The correlation between the averages obtained by women in each unit of the Federation and the sanitation conditions in these regions reinforces this idea: in areas where there was a greater proportion of women living in houses without a bathroom, the expected averages of ENEM scores were also lower. On the other hand, in areas where there was a greater proportion of women with access to sewage collection services, the expected averages of the ENEM scores were higher.

 
 
 

Economic Performance

 
 
 

The economic life of Brazilian women is also strongly influenced by access to basic sanitation. As it was presented in Chapter 1 of this study, there were 39.3 million women employed in Brazil in 2016. That was equivalent to 86.9% of the female labor force. The unemployment rate, as mentioned earlier, reached 13.1% of the workforce, a higher proportion than men. The highest rates of unemployment in the female population were registered in the Northeast and North regions of the country. In the Southeast of Brazil, the unemployment rate reached 13.5% of the female labor force. In this result, the high unemployment rates in the metropolitan areas of the states weighed heavily: around the Southeast capitals unemployment rates were between 16.4% and 18.2% of their respective female labor forces. Table A.13 of the Statistical Annex details these statistics by region of the country.

The remuneration of all occupations in economic activities carried out by Brazilian women reached an average of R$ 1,826.35 per month in 2016. As shown in Table A.14 of the Statistical Annex, the levels of remuneration were higher in the South and Midwest regions of the country. However, in the South, the sums received were more homogeneous; in the Midwest, the high average sum resulted from the relatively high salaries paid in Brasilia. The average remuneration earned in the capitals of the Brazilian states was 39.2% higher than in the other areas. The capitals of the Southeast registered higher salaries than the country's average, followed by the capitals of the South and Midwest regions.


Graph 4.11
Average monthly salary, by gender and self-declared race, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Graph 4.12
Average monthly salary, by gender and maternity status, 2016

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017. Elaboration: Ex Ante Consultoria Econômica.

The most striking point in Table A.14, however, is the existence of a large pay gap between men and women. On average in the country, women received a remuneration of 22.9% less than that of men in 2016. It is worth mentioning that the pay gap between men and women is high in all areas (urban or rural, in the capitals or in the interior) and in all Brazilian states. There have been rare cases where women have earned the same or more than men.

These large pay gaps are at the heart of the issue of gender inequality in the country. One striking feature is the fact that the pay gap between men and women is greater among the populations of self-declared of Asian descent and white people. In these cases, the gaps between the incomes of men and women reach 39.3% and 27.1%, respectively. In black or multiracial self-reported populations, income gaps are around 20%.

Table 4.2
Expected salary of women living in households without sanitation compared to those living in households with sanitation, Brazil, 2016

Water treated by general network *Collection of sewage by general networkBathroom for exclusive use
White-29.7%-23.3%-62.8%
Black-24.4%-23.1%-63.2%
Of Asian descent-30.3%-40.7%-82.0%
Multiracial-23.6%-20.2%-59.3%
Indigenous-16.3%-16.9%-59.9%
Employees in the private sector-28.2%-28.5%-54.8%
Domestic Workers-25.7%-22.4%-52.7%
Employees in the public sector-29.7%-24.5%-60.1%
Business Women-34.4%-28.3%-27.1%
Self-employed-34.7%-32.9%-70.3%
Average-26.5%-21.9%-61.3%

Source: IBGE, 2017(*) With regular supply. Elaboration: Ex Ante Consultoria Econômica

Considering only the female population, it was noted that there were strong differences between the remuneration of women with and without children or underage step children living in their homes. However, the differences varied widely according to race. In self-declaring Asian-descent women's groups, women with children or stepchildren living with them earned more than those who did not have children or stepchildren living together. Something similar, but on a smaller scale, was observed in the group of white self-declared women. Among the self-reported black, multiracial and indigenous women, the highest wages were among the groups of women without children or stepchildren living with them. These facts suggest that motherhood has different effects on the remuneration of women in different groups.

Table 4.3
Expected salary of men living in households without sanitation in relation to those living in households with sanitation, Brazil, 2016

Water treated by general network *Collection of sewage by general networkBathroom for exclusive use
White-37.4%-29.0%-66.7%
Black-29.0%-30.7%-66.9%
Of Asian descent-36.2%-45.2%-79.7%
Multiracial-33.7%-26.1%-63.6%
Indigenous-30.3%-37.5%-65.8%
Employees in the private sector-34.6%-32.1%-63.5%
Domestic workers-26.2%-23.8%-51.4%
Employees in the public sector-30.4%-28.5%-67.5%
Businessmen-33.4%-31.4%-65.8%
Self-employed-39.7%-32.6%-65.1%
Average-34.9%-27.9%-65.3%

Source: IBGE, 2017(*) With regular supply. Elaboration: Ex Ante Consultoria Econômica

Again in the comparison between genders, it is observed that the differences occur in almost all types of occupation, that is, it is not a phenomenon restricted to the spectrum of the private work relations. The average remuneration of Brazilian women entrepreneurs was 32.8% lower than that of men in the same occupation. For self-employed women, the differential reached 21.5%. Even in the public career, where labor relations are governed by distinct rules, women earned 30.9% less than men.

Graph 4.13
Monthly average salary, by gender and type of occupation, 2016

Source: IBGE, 2017 (*) Includes banked and CLT servers. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017 (*) Includes banked and CLT servers. Elaboration: Ex Ante Consultoria Econômica.

According to data from the PNADC of 2016, access to sanitation was once again a variable that determines the differences. Considering only the female population, the average remuneration of women residing in housing without access to treated water was 36.9% lower than that of women living in households with access to this service. The female population living in housing without sewage collection through the general network earned, on average, 34.8% less income than women who lived in homes connected to the general sewage collection network. The absence of a bathroom had an even greater influence: the average remuneration of women who lived in houses without a private bathroom was 73.2% lower than that of women who lived in houses with bathrooms.

Graph 4.14
Monthly average salary, by gender and access to sanitation, 2016

Source: IBGE, 2017 (*) Includes banked and CLT sworkerservers. Elaboration: Ex Ante Consultoria Econômica.

Source: IBGE, 2017 (*) Includes banked and CLT sworkerservers. Elaboration: Ex Ante Consultoria Econômica.

To find the factors explaining the huge pay gaps and to calculate the partial effect of sanitation on women's income, statistical models were developed based on the PNADC data for 2016. The models, which are presented in detail in the Methodological Annex, have taken into account a large body of information about people and their households to explain the average hourly pay of the individuals in the sample. Regarding the characteristics of the houses, the location (state, area and region), the materials of the walls and roofs, the sanitation conditions (adequate water, sewage collection and bathroom existence) and the trash collection system were observed. Regarding the characteristics of the people, the gender, age, declared race, education, type of occupation, economic sector of the person in question, the person's role in the household (head, spouse, etc.) and, in the case of women, the fact that she is a mother with underage children or stepchildren.

The partial effects corroborate the ideas developed in several studies in the Brazilian and international literature and show the existence of very high pay gaps. Taking as reference two persons with similar characteristics who live in equal conditions, but who differ in gender, the income gap between men and women is estimated: in 2016, the expected income of the female population was 22.9% lower than that of the male population. Among women, the self-reported blacks, multiracial and indigenous observed much lower wages than the self-declared white and of Asian descent. As expected, schooling positively affected earnings and age had a positive but decreasing effect.

With regard to sanitation, the results reinforce the findings of the Instituto Trata Brasil study (2017). People who lived in houses without a bathroom saw an average remuneration 21.5% lower than that of people living in houses with a bathroom. The lack of sewage collection reduced the average pay by almost 7% and the lack of adequate access to treated water by 3.1%. One person, regardless of gender, living in a house without a bathroom, without water and without sewage collection should expect an income almost 32% lower than that of a person living in a house with treated water, sewage collection and bathroom.

Table 4.2 shows the expected remuneration differences between women living in households without access to basic sanitation and those living in housing with access to basic sanitation, considering the self-reported race and the occupation situation. Estimates show that, with the remaining factors staying constant, it is expected that a woman living in a non-bathroom household will have a 61.3% lower income than a woman living in house with a bathroom of exclusive use. In the case of a woman living in housing without sewage collection, the expected remuneration is 21.9% lower than that of women residing in housing with access to the general sewage collection network. If the woman does not have treated water in her house, she can expect a remuneration of 26.5% less than that of the female population residing in houses with regular water supply through the general network.

Among men, there are also large differences in expected remuneration according to the availability of sanitation in housing. For example, for the male group, the absence of treated water reduces expected income by 34.9%. In the case of the absence of sewage collection in the household, the expected remuneration difference is 27.9%. The absence of a bathroom in the house reduces the expected remuneration of a man by 65.3%.